WO2009137441A1 - Procédés et appareil de détection/classement de cibles radar, notamment d’oiseaux et d’autres dangers - Google Patents

Procédés et appareil de détection/classement de cibles radar, notamment d’oiseaux et d’autres dangers Download PDF

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Publication number
WO2009137441A1
WO2009137441A1 PCT/US2009/042789 US2009042789W WO2009137441A1 WO 2009137441 A1 WO2009137441 A1 WO 2009137441A1 US 2009042789 W US2009042789 W US 2009042789W WO 2009137441 A1 WO2009137441 A1 WO 2009137441A1
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WO
WIPO (PCT)
Prior art keywords
channel
data
target
weather
polarization
Prior art date
Application number
PCT/US2009/042789
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English (en)
Inventor
Peter R. Drake
Yuchoi F. Lok
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Raytheon Company
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Raytheon Company filed Critical Raytheon Company
Priority to AU2009244465A priority Critical patent/AU2009244465B2/en
Priority to CA2723682A priority patent/CA2723682C/fr
Priority to EP09743427A priority patent/EP2294444A1/fr
Publication of WO2009137441A1 publication Critical patent/WO2009137441A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/024—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using polarisation effects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/42—Simultaneous measurement of distance and other co-ordinates
    • G01S13/424—Stacked beam radar
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/411—Identification of targets based on measurements of radar reflectivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/411—Identification of targets based on measurements of radar reflectivity
    • G01S7/412—Identification of targets based on measurements of radar reflectivity based on a comparison between measured values and known or stored values
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Definitions

  • the present invention provides methods and apparatus for classifying targets, such as birds and aircraft, from altitude estimation and polarimetric data including differential phase and differential reflectivity data.
  • targets such as birds and aircraft
  • polarimetric data including differential phase and differential reflectivity data.
  • weather and target channel data having different polarizations are used to obtain the polarimetric data.
  • aircraft hazards such as migrating birds can be avoided. While exemplary embodiments are shown having various channel configurations and polarizations, it is understood that modifications can be made to meet the needs of a particular application without departing from the scope of the present invention.
  • a system comprises an antenna, a target channel including: a low beam receiver channel, a high beam receiver channel, and a weather receiver channel, and a signal processor to receive data from the low beam channel, the high beam channel and the weather channel for performing an altitude estimation based upon a target amplitude ratio between the low beam channel and the high beam channel and target range, and for performing target classification by calculating polarimetric parameters from the target data and the weather data including differential reflectivity and differential phase data, wherein the target channel has a different polarization than the weather channel.
  • the system can further including one or more of the following features: the altitude estimation is obtained over multiple scans, the differential reflectivity and the differential phase are obtained from co -polarization data and reverse polarization data, the signal processor generates probability values for a target, the probability values correspond to at least birds and aircraft, the differential reflectivity is defined as:
  • ⁇ DR where R is range, l c and Q c are the in-phase and quadrature data of the co-polarization channel, and /, and Q 1 are the in-phase and quadrature data of the reverse polarization channel, and the weather channel data and the target channel data are processed in the same radar dwell for simultaneous polarimetric data.
  • a method comprises receiving radar return at a target channel and a weather channel, wherein the target channel includes a low beam receiver channel and a high beam receiver channel, transforming the radar return in a signal processor and memory including processing data from the low beam channel, the high beam channel and the weather channel to generate altitude estimation data based upon a target amplitude ratio between the low beam channel and the high beam channel and target range, and transforming the radar return comprising performing target classification by calculating polarimetric parameters from the target data and the weather data including differential reflectivity and differential phase data, wherein the target channel has a different polarization than the weather channel .
  • an article comprises a computer readable medium comprising stored instructions that enable a machine to perform the steps of: receiving radar return at a target channel and a weather channel, wherein the target channel includes a low beam receiver channel and a high beam receiver channel, transforming the radar return in a signal processor and memory including processing data from the low beam channel, the high beam channel and the weather channel to generate altitude estimation data based upon a target amplitude ratio between the low beam channel and the high beam channel and target range, and transforming the radar return comprising performing target classification by calculating polarimetric parameters from the target data and the weather data including differential reflectivity and differential phase data, wherein the target channel has a different polarization than the weather channel.
  • FIG. 1 is a schematic representation of a system providing target classification in accordance with exemplary embodiments of the invention
  • FIG. 2 is a block diagram showing additional detail for the system of FIG. 1 ;
  • FIG. 3 is a block diagram showing additional detail for the system of FIG. 2;
  • FIG. 4 is a graphical representation of the method for generating the amplitude ratio versus altitude lookup table
  • FIG. 5 is a flow diagram showing exemplary altitude estimating processing
  • FIG. 5 A is a graphical representation of smoothed high beam amplitude ratio data
  • FIG. 6 is a flow diagram showing exemplary inphase and quadrature data processing
  • FIG. 7 is a flow diagram of exemplary probability processing
  • FIG. 8 is a graphical representation of altitude estimation versus range
  • FIG. 9 is a mapping of amplitude ratio versus phase difference for an aircraft at 33 kft.
  • FIG. 10 is a mapping of amplitude ratio versus phase difference for a possible bird migration.
  • method and apparatus for air clutter detection exploit weather and high/low beam target channels of a terminal S-band ASR air traffic control radar, e.g., 2700 MHZ to 2900 MHz, to create polarimetric data and altitude estimation.
  • a terminal S-band ASR air traffic control radar e.g., 2700 MHZ to 2900 MHz
  • the system can classify detections as fixed-wing aircraft, rotary-wing aircraft, birds, insects, rain, hail, false alarms due to ground traffic, wind farm induced clutter, anomalous propagation induced clutter, and the like.
  • air clutter detection is provided as part of an en-route L- band system.
  • the inventive system determines polarimetic signatures to distinguish between aircraft and birds, for example.
  • the system has a target channel and a weather channel.
  • the weather channel is a different polarization from that of the target channel, and the channels are processed in separate receiver-signal processor channels.
  • the weather channel provides precipitation reflectivity.
  • the weather channel data is processed in a similar manner to the target channel data.
  • the amplitude ratio and phase difference between the target and weather channel data can be calculated with the resultant amplitude-phase factors providing distinguishing target characteristics. Since the system includes high and low beams, the system can be used as in a mono-pulse radar to estimate target altitude by simultaneously processing the high and low beam data.
  • FIG. 1 shows an exemplary system 100 for air clutter detection in accordance with exemplary embodiments of the invention.
  • a pedestal 10 includes a motor 12 and encoder 14 coupled to a pedestal controller 16.
  • a transmitter 18 is coupled to a rotary joint 20 providing a weather channel 22 and low beam and high beam target channels 24, 26 to an antenna assembly 28.
  • the rotary joint 20 is coupled to a first RF assembly 30 and a second RF assembly 40, each having a target low beam module 32, 42, a target high beam module 34, 44, and a weather module 36, 46.
  • a first receiver/exciter 50 and a second receiver/exciter 60 each include down converter modules 52, 54, 56, 62, 64, 66 and local oscillators 58, 68 for the respective low beam, high beam, and weather signals.
  • the downconverted signals are provided to first and second signal processors 70, 80, which are both coupled to first and second radar data processors 82, 84 via first and second local area networks (LANs) 86, 88, for example.
  • the system 100 can include features of air traffic control systems that have an independent weather channel and target channel. Weather related false alarms in the target channel are typically not suppressed by checking against the detection of precipitation in the weather channel. Such weather channel reports are also not processed in such a manner as to be able to discern whether the precipitation type is rain, hail or
  • the inventive system 100 uses data from both the weather high and low beam channels and target high and low beam channels to detect and classify detections.
  • the system takes advantage of the different polarization between the weather and the target channels to provide polarimetric data.
  • the low and high beam of the target channels provide altitude information. Together with the Doppler and reflectivity information, the system 100 is thus capable of classifying detections and becomes an integrated detection classification system for air traffic control use.
  • the signal processor uses the high beam data in the short pulse range, e.g., in the order of 0.5 to 6.5 nmi to avoid the ground clutter, and switches at a predefined range, e.g., 6.5 nmi, to the low beam for complete altitude coverage.
  • the system 100 includes a multi-channel, e.g., seven, rotary joint 20 to enable both the high beam data and the low beam data to be processed concurrently over the full instrument range.
  • the system For each detection in the low beam data, the system searches for a corresponding detection in the high beam data at the same range.
  • the altitude of the detection is estimated using a lookup table with the target amplitude ratio between the two beams as one of the indexes and the range as the other.
  • An exemplary altitude estimation technique is shown and described by H. R. Ward in U.S. Patent No. 4,961,075, which is incorporated herein by reference.
  • the estimated altitude of the detection is useful for separating aircraft from false alarms due to moving clutter, such as birds, weather, etc., ground traffic and wind farms.
  • the system 100 also performs target detection using the weather channel data. Since the weather channel data is of a different polarization to the target channel, the differential reflectivity, differential phase and correlation coefficient between the two polarization data can be calculated. According to D. S. Zrnic, birds and insects have differential reflectivity between 2 and 9 dB and differential phase about 25 degrees; ground clutter has large differential reflectivity but has a zero mean value; weather has low differential reflectivity and phase but has high correlation coefficient. Discrimination between birds and insects is possible because insects tend to have higher differential reflectivity, while birds have higher differential phase.
  • FIG. 2 shows an exemplary system 200 having target classification in accordance with exemplary embodiments of the invention.
  • the system 200 includes a high beam channel 202 and a low beam channel 204 providing data to an altitude estimation module 206.
  • the altitude estimation module 206 outputs altitude 208 and reflectivity 210 information to statistical classifier module 212.
  • the altitude estimation module 206 provides phase information 214 to a polarimetric data module 216, and also receives data from a weather channel detection module 218 and the reflectivity information 220 from the altitude estimation module 206.
  • the polarimetric data module 216 provides differential reflectivity information, differential phase information, and correlation coefficient information to the statistical classifier module 212.
  • the polarimetric characteristics are used as detection features. Together with the estimated altitude these features are mapped to the statistics of the known detection classes, which include aircraft types, weather types, birds, insects and false alarm types. These statistics form a multi-dimensional "training database.” During normal operation, the measured features are mapped to the training database to read out the detection classes. The highest class with the highest population is selected as the result and the population count is converted to a confidence factor. The confidence factors over multiple radar scans are accumulated for the detections and the conferred results are reported to the air traffic control display. The implementation of such statistical classifier could be similar to the one used in reference.
  • FIG. 3 shows further details 300 of the system 200 of FIG. 2.
  • data is processed by a series of modules including a Doppler filter module 304, and log-magnitude calculation module 306.
  • a CFAR (Constant False Alarm Rate) detection module 308 is coupled to a binary integration module 310, which provides an output to an altitude estimation module 312.
  • the altitude estimation module 312 and altitude database 314 are described more fully below.
  • Binary integration data (peak detection range and filter) is provided to a log- magnitude calculation module 316 for the high beam target channel and to a module to calculate polarimetric parameters 318.
  • the high beam target channel path includes a Doppler filter module 322, which is coupled to the log magnitude calculation module 316.
  • the low beam weather channel data is processed by a pulse compression module 324 and a filter module 326.
  • a clutter map module 328, a filter selection module 330, and a clear day coefficient selection module 332 are coupled in parallel and exchange information with the filter module 326.
  • a weather map module 334 receives the filtered data and provides a series of outputs to a merge module 336, which provides output data to a weather contour module 338 coupled to a radar data processor.
  • the module 318 to calculate polarimetric parameters receives target I and Q data from the high beam target pulse compression module 320 and weather I and Q data from the weather channel pulse compression module 324 and generates phase and reflectivity ratio information, as described more fully below. This information is provided to a statistical target classifier module 342, which receives data from a trained database 343, outputting detection range, azimuth, altitude, target type, and confidence information provided to an RDP.
  • the high beam data and low beam data pair are extracted along with the Mode-C code.
  • An amplitude ratio for the high and low beam data is calculated for a target range to generate an amplitude ratio table at the altitude given by the Mode-C code, as shown.
  • a 3x32 cells operator 32 range columns and 3 altitude rows
  • the table is then smoothed before being used for altitude estimation.
  • FIG. 4B shows the smoothed amplitude ratio versus altitude curve for the range of 30 nmi.
  • FIG. 5 shows an exemplary sequence of steps for estimating altitude in accordance with exemplary embodiments of the invention.
  • step 500 the amplitude ratio is determined for a given range from the high beam signal over the low beam signal.
  • step 502 it is determined whether the amplitude ratio is less than a low threshold value. If so, no estimation is performed in step 504. If not, then it is determined in step 506 whether the amplitude ratio is greater than a high threshold. If so, no altitude estimation is performed. If not, in step 508, the amplitude ratio is rounded to an index value.
  • step 510 an altitude estimation and confidence value are generated from a table, such as the table of FIG. 4A, from the range and index values.
  • the target altitude is estimated at 100 foot intervals with a confidence factor ranging from 0 to 1.
  • the confidence factor can be pre-calculated in the table based on the standard deviation of the altitude value at the given amplitude ratio before smoothing was applied, for example. It is understood that the granularity of the altitude estimate can vary to meet the needs of a particular application and the information obtainable from the radar system.
  • FIG. 5 A shows an exemplary plot of amplitude ratio versus altitude at various ranges, shown as 10, 20, 30, 40, and 50 nautical miles (nmi) for exemplary data. It is understood that the plotted data is smoothed. The approximate threshold values, AH and AL, are also shown in FIG. 5 A marking the linear portion of the smoothed data.
  • FIG. 6 shows an exemplary sequence of steps for polarimetric parameter calculation in accordance with exemplary embodiments of the invention.
  • Ic, Qc, co-polarization data, and Ir, Qr reverse polarization data in step 600 I and Q data is selected from the specified range R.
  • FIG. 7 shows an exemplary sequence of steps for statistical target classification.
  • step 700 for given range R, estimated altitude Alt, differential reflectivity Z DR , and differential phase ⁇ DR , integer values i r , i a , i z , and i d , are generated in step 702 to generate probability values.
  • a probability of the target being an aircraft P tgt is computed from a table using values tgt, i r , i a , h, i d -
  • the indexes tgt, wx, bird and cltr represent four separate tables that form the trained database filled with measured data from known objects such as aircraft (tgt), weather (wx), birds (bird) and ground clutter (cltr).
  • a probability of a target being a weather-related false alarm is determined from a table based on values for wx, i I: i a , i 2 , i d .
  • the probability of a target being birds is determined from bird, i r , i a , i z , i d and the probability of a target being ground clutter related false alarm is determined from cltr, i r , i a , i z , id.
  • the amplitude ratio (ZD R ) and phase difference ( ⁇ DR ) between the target and weather channel data can be calculated to distinguish target characteristics.
  • a DASR system such as the system 100 of FIG. 1, has a target and a weather channel.
  • the weather channel is a different polarization to the target channel, and they are processed in separate receiver-signal processor channels.
  • the DASR weather channel determines precipitation reflectivity.
  • the weather channel data is processed in a similar manner to the target channel data. This approach provides simultaneous polarimetric data, which is an improvement over polarimetric data in alternative radar dwells.
  • the amplitude ratio (Z DR ) and phase difference ( ⁇ DR ) between the target and weather channel data can be calculated as follows: where R is range, I c and Q c are the in-phase and quadrature data of the co-polarization channel, and /, and Q 1 are the in-phase and quadrature data of the reverse polarization channel.
  • FIG. 3 shows an exemplary system having illustrative processing modules.
  • FIG. 8 shows an example of estimated target altitude in comparison with the target altitude from the beacon radar.
  • the altitude estimations (dots) have deviation from the beacon radar reported altitude (Mode C ode). Smoothing the altitude estimations over 13 scans, for example, provides a more accurate estimation of the target altitude.
  • the RMS error is 240 ft.
  • FIG 9 shows the distinct features of an aircraft and FIG. 10 shows possible bird data expressed in amplitude ratio versus phase difference maps based upon collected data.
  • FIG. 9 shows the peak of the distribution at 0 degree phase difference and 6 dB amplitude ratio.
  • the bird data in FIG. 10 has a peak of the distribution at 30 degrees phase difference and 9 dB amplitude ratio. It should be noted that the distribution in FIG. 10 has wider spread than FIG. 9.
  • Exemplary embodiments of the invention use amplitude ratio, phase difference, estimated target altitude and target velocity, for target classification to distinguish aircraft from birds and precipitation.
  • radar systems can include inventive target classification.
  • polarizations can be used in various embodiments. Exemplary polarizations include linear polarization (transmission in vertical polarization, channel A received in elliptical polarization, channel B received in vertical polarization), circular polarization (transmission in circular polarization, channel A received in circular co-polarization, and channel B received in circular reverse polarization).
  • linear polarization transmission in vertical polarization, channel A received in elliptical polarization, channel B received in vertical polarization
  • circular polarization transmission in circular polarization, channel A received in circular co-polarization, and channel B received in circular reverse polarization
  • circular polarimetric data shows clear differences between channels and target types. It is understood that further polarization configurations are possible.

Abstract

Cette invention se rapporte à des procédés et à un appareil destinés à traiter des données à partir d'un canal de faisceau faible, d'un canal de faisceau élevé et d'un canal de conditions atmosphériques de manière à procéder à une estimation d'altitude sur la base d'un rapport d'amplitude de cible entre le canal de faisceau faible et le canal de faisceau élevé et une distance de cible, et à effectuer une détection de cible sur la base des données qui proviennent du canal de conditions atmosphériques. Dans un mode de réalisation, il est possible de détecter et de classer des oiseaux migrateurs de manière plus précise qu'avec des systèmes conventionnels.
PCT/US2009/042789 2008-05-05 2009-05-05 Procédés et appareil de détection/classement de cibles radar, notamment d’oiseaux et d’autres dangers WO2009137441A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
AU2009244465A AU2009244465B2 (en) 2008-05-05 2009-05-05 Methods and apparatus for detection/classification of radar targets including birds and other hazards
CA2723682A CA2723682C (fr) 2008-05-05 2009-05-05 Procedes et appareil de detection/classement de cibles radar, notamment d'oiseaux et d'autres dangers
EP09743427A EP2294444A1 (fr) 2008-05-05 2009-05-05 Procédés et appareil de détection/classement de cibles radar, notamment d oiseaux et d autres dangers

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US5040208P 2008-05-05 2008-05-05
US61/050,402 2008-05-05

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US (1) US7948429B2 (fr)
EP (1) EP2294444A1 (fr)
CA (1) CA2723682C (fr)
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